AudioAlign is a tool that I started developing in 2010 for my master’s thesis (and has been actively developed since then), with the goal to create a software for the automatic synchronization of audio and video recordings. Although I never quite reached the point of a fully automatic synchronization system, it showed promising results compared to the few similar commercial applications available on the market, and continues to be a helpful tool for my research purposes. I gave up on the plan to commercialize it due to patenting problems I didn’t know how to deal with, but instead decided on open sourcing it so others could still make use of it and hopefully even help me improve it. Aurio is a library extracted from AudioAlign, providing the underlying core audio processing functionality like an audio processing engine and audio fingerprinting and time warping algorithms. Both Aurio and AudioAlign are now available as AGPL licensed open source software on GitHub.

Conducting high precision audio drift or audio frequency measurements doesn’t have to be expensive. In this guide, I’m showing you how to do it with an ordinary computer, an audio interface, a GPS receiver, and a little bit of tinkering.

Conducting high precision audio drift or audio frequency measurements doesn’t have to be expensive. In this guide, I’m showing you how to do it with an ordinary computer, an audio interface, a GPS receiver, and a little bit of tinkering.

The ITEC MediaPlayer library is a lightweight VideoView/MediaPlayer replacement for Android’s default components, enhancing it with exact frame seek, playback speed adjustment, GLES shader effects, picture zoom/pan by gestures, and DASH support. The source code and a more detailed description is now available on GitHub, its accompanying demo showcase app on the Google Play Store.

Over the last year, I’ve been extensively researching and wasting time on an effect called clock drift in the multimedia domain. Clock drift is the deviation of a clock’s speed from the word time standard‘s speed, resulting in shifts in sampling rates, and this shift leads to parallel recordings from different devices not being synchronizable without manual post-processing. Because each recording is sampled a bit differently, they all run at a slightly different speed when played back in parallel on a single device, like it happens in a non-linear editing system on a computer workstation. To conclude this topic, I have just published an Android app called ClockDrift, which helps to measure drift in multimedia devices. I have also written an accompanying ClockDrift App User Guide and a general introduction into the topic, Clock Drift in Multimedia Recordings.